<p><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/5a8b9bb0-797e-4d21-b621-f3708cd544b7"></p><h3><strong>Overview</strong></h3><p>Human face conveys a significant information about identity, age, gender, emotion, and ethnicity. It is a key demographic and a soft biometric trait for human identification. Ages are also important in the face-to-face communication between humans. Facial features influence one person’s attraction to another. They can signal cues to fertility and health. Therefore, these factors can increase a person’s productivity and success.</p><p>Age is one of the facial attributes which plays a significant role in helping or hindering communication. Like culture, beliefs, experience, language, age can affect both how we say what we mean, as well as how we interpret what others mean. It is a factor that influences how we communicate with each other, and can act as a barrier, along with many other factors. In a study which came out of the university of Pennsylvania and which analyses the vocabulary of 75000 facebook users, researchers showed that the vocabulary of a person can predict his/her age (Schwartz et al., 2013).</p><p>Raising the ability of a machine to recognize and interpret faces and facial traits such as age in real time can improve the interaction between humans and machines. Many researchers pay attention to the automatic interpretation of face images. Consequently, systems to identify faces and gender, estimate age and recognize emotions, have been developed.</p><h3><strong>Need to know</strong></h3><p>You need to upload image face to predict.</p>

Age Estimation

<p><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/b01ddd08-bdf6-4b6a-ba68-9dce2a53599f"></p><h3><strong>Overview</strong></h3><p>If you are looking for an online weight loss calculator which shows the accurate time (weeks or months) need to achieve a specific weight loss goal, this is it. Calculate the time for healthy and fast weight loss and the required calorie intake on a daily or weekly basis. This is a weight loss calculator for men and women.</p><p>This Weight loss calculator is easy to use. Enter your age, height, weight, weight goal and time span to achieve goal. The calculator will give you accurate results along with a weight loss chart to understand the effect of calorie intake on weight loss.</p><p><span style="color: rgba(0, 0, 0, 0.8);">Following a strict weight loss program often lets you acheive your desired weight goal. However, understanding your daily calorie requirement and planning a weight loss diet accordingly is something what people often fail at. The Weight Loss Calculator here is a useful tool which comes in handy when you are planning to reduce weight. Find your daily and weekly calorie needs and also find out how long it will take to reduce kilos/pounds in a healthy and safe way.</span></p><h3><strong style="color: rgba(0, 0, 0, 0.8);">Need to know</strong></h3><p>You need to fill in the necessary metrics for the calculation.</p>

Caculate Total Calories To Lose Weight

Caculate total calories you need every day to lose weight


<p><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/70742646-3828-442f-b191-4cc7357173d5"></p><h3><strong>Overview</strong></h3><p><span style="color: rgb(0, 0, 0);">Face emotion classification from facial image with DMUE</span></p><h3><strong style="color: rgb(0, 0, 0);">Need to know</strong></h3><p>You need to upload face image to predict</p><p><br></p><p><br></p>

Face Emotion Classification

Face emotion classification from facial image with DMUE

<p><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/7eb97262-01d2-4aca-ad84-26ab646ff084"></p><h3><strong>Overview</strong></h3><p>The task of age transformation illustrates the change of an individual's appearance over time. Accurately modeling this complex transformation over an input facial image is extremely challenging as it requires making convincing and possibly large changes to facial features and head shape, while still preserving the input identity. In this work, we present an image-to-image translation method that learns to directly encode real facial images into the latent space of a pre-trained unconditional GAN (e.g., StyleGAN) subject to a given aging shift. We employ a pre-trained age regression network used to explicitly guide the encoder to generate the latent codes corresponding to the desired age. In this formulation, our method approaches the continuous aging process as a regression task between the input age and desired target age, providing fine-grained control on the generated image. Moreover, unlike other approaches that operate solely in the latent space using a prior on the path controlling age, our method learns a more disentangled, non-linear path. We demonstrate that the end-to-end nature of our approach, coupled with the rich semantic latent space of StyleGAN, allows for further editing of the generated images. Qualitative and quantitative evaluations show the advantages of our method compared to state-of-the-art approaches.</p><h3><strong>Need to know</strong></h3><p>You need to upload image face to transformation.</p><p><br></p>

Face Aging Transformation

Face aging transformation from facial image with SAM




<p><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/c21513b6-a182-4141-9b7e-a6eda71837ef"></p><h3><strong>Overview</strong></h3><p>Thus preventing Heart diseases has become more than necessary. Good data-driven systems for predicting heart diseases can improve the entire research and prevention process, making sure that more people can live healthy lives. This is where Machine Learning comes into play. Machine Learning helps in predicting the Heart diseases, and the predictions made are quite accurate.</p><h3><strong>Need to know</strong></h3><p><span style="color: rgb(24, 24, 24);">You need to fill </span>necessary information<span style="color: rgb(24, 24, 24);"> to predict .</span></p><p><br></p>

Heart Disease Detection

Heart disease detection from attributes of patient with Random Forest


<p><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/141948ea-3823-4852-ab6d-26ac582512b8"></p><h3><strong>Overview</strong></h3><p>Malaria is a serious and sometimes fatal disease caused by a parasite that commonly infects a certain type of mosquito which feeds on humans. People who get malaria are typically very sick with high fevers, shaking chills, and flu-like illnesses. This service will help you detect malaria early by predicting through cell imaging.</p><h3><strong>Need to know</strong></h3><p>You need to upload cell image for prediction</p>

Malaria Disease Prediction

Malaria disease prediction from cell images with CNN


<p><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/2efb5fb7-bf88-4918-b34c-1713300ecb7f"></p><h3><strong>Overview</strong></h3><p>Finds out symptoms similar to a given symptom, from a symptom-disease data set.</p><p>This model is used to predict symptoms that are closely related to a given sign. It can be used in cases (read apps) where the user enters a symptom. A list of similar symptoms pops up, of which the user can select the ones he's suffering from. These can be further fed into a model that can then predict the disease the person is suffering from, and redirect him to the associated specialist.</p><h3><strong>Need to know</strong></h3><p>You need to fill symptom to predict .</p>

Frequent Diseases Detection 

Frequent diseases detection based on symtoms with Decision Tree

Pneumonia and Covid Detection

COVID-19, pneumonia detection From Chest CT Image with COVID-Net CT

<p><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/a1be2773-8bc8-4c25-9aec-ad52cbdf4d19"></p><h3><strong>Overview</strong></h3><p>The service detect 23 types of skin diseases .<span style="color: rgba(0, 0, 0, 0.7);">The categories include acne, melanoma, Eczema, Seborrheic Keratoses, Tinea Ringworm, Bullous disease, Poison Ivy, Psoriasis, Vascular Tumors, etc.</span></p><h3><strong style="color: rgba(0, 0, 0, 0.7);">Need to know</strong></h3><p>You need to upload frequent skin image to predict.</p><p><br></p>

Frequent Skin Diseases Classification 

Frequent skin diseases classification from image with RestNet

<p><br></p><h3><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/b6fe7e34-8dd1-402d-a7f2-e3378cd0ecac"></h3><h3><strong>Overview</strong></h3><p>This article introduce the method of scoring facial beauty using deep learning.</p><h3><strong>Need to know</strong></h3><p>You need to upload face image to scoring</p>

Facial Beauty Scoring

Facial beauty scoring from facial image with HMTNet

<p><br></p><p><img class="thumb" fetchpriority="high" data-pin-no-hover="true" src="https://img.freepik.com/free-vector/skin-problems-infographics-scheme-with-fixing-pimples-black-heads-wrinkles-acne-allergy-dark-circles-areas-flat-vector-illustration_1284-72723.jpg?t=st=1672284252~exp=1672284852~hmac=302a4e4aee4990ed4e7b9f4777e06c91a30a636cbd257e2eee615f3337ac9395" sizes="(max-width: 479px) 100vw, (min-aspect-ratio: 626/417) calc((100vh - 184px) * 1.501199040767386), (max-width: 1095px) calc(100vw - 40px), calc(100vw - 540px)" width="420" height="279.77635782747603" alt="Free vector skin problems infographics scheme with fixing pimples black heads wrinkles acne allergy dark circles areas flat vector illustration" style="max-width: calc((100vh - 184px) * 1.5012); display: block; margin: auto;" srcset="https://img.freepik.com/free-vector/skin-problems-infographics-scheme-with-fixing-pimples-black-heads-wrinkles-acne-allergy-dark-circles-areas-flat-vector-illustration_1284-72723.jpg?w=360&amp;t=st=1672284259~exp=1672284859~hmac=a236fff8286951f71734499ee0c6acbf29ff7717268712e50fdcf7df8280cc7e 360w, https://img.freepik.com/free-vector/skin-problems-infographics-scheme-with-fixing-pimples-black-heads-wrinkles-acne-allergy-dark-circles-areas-flat-vector-illustration_1284-72723.jpg?w=740&amp;t=st=1672284259~exp=1672284859~hmac=a236fff8286951f71734499ee0c6acbf29ff7717268712e50fdcf7df8280cc7e 740w, https://img.freepik.com/free-vector/skin-problems-infographics-scheme-with-fixing-pimples-black-heads-wrinkles-acne-allergy-dark-circles-areas-flat-vector-illustration_1284-72723.jpg?w=826&amp;t=st=1672284259~exp=1672284859~hmac=a236fff8286951f71734499ee0c6acbf29ff7717268712e50fdcf7df8280cc7e 826w, https://img.freepik.com/free-vector/skin-problems-infographics-scheme-with-fixing-pimples-black-heads-wrinkles-acne-allergy-dark-circles-areas-flat-vector-illustration_1284-72723.jpg?w=900&amp;t=st=1672284259~exp=1672284859~hmac=a236fff8286951f71734499ee0c6acbf29ff7717268712e50fdcf7df8280cc7e 900w, https://img.freepik.com/free-vector/skin-problems-infographics-scheme-with-fixing-pimples-black-heads-wrinkles-acne-allergy-dark-circles-areas-flat-vector-illustration_1284-72723.jpg?w=996&amp;t=st=1672284259~exp=1672284859~hmac=a236fff8286951f71734499ee0c6acbf29ff7717268712e50fdcf7df8280cc7e 996w, https://img.freepik.com/free-vector/skin-problems-infographics-scheme-with-fixing-pimples-black-heads-wrinkles-acne-allergy-dark-circles-areas-flat-vector-illustration_1284-72723.jpg?w=1060&amp;t=st=1672284259~exp=1672284859~hmac=a236fff8286951f71734499ee0c6acbf29ff7717268712e50fdcf7df8280cc7e 1060w, https://img.freepik.com/free-vector/skin-problems-infographics-scheme-with-fixing-pimples-black-heads-wrinkles-acne-allergy-dark-circles-areas-flat-vector-illustration_1284-72723.jpg?w=1380&amp;t=st=1672284259~exp=1672284859~hmac=a236fff8286951f71734499ee0c6acbf29ff7717268712e50fdcf7df8280cc7e 1380w, https://img.freepik.com/free-vector/skin-problems-infographics-scheme-with-fixing-pimples-black-heads-wrinkles-acne-allergy-dark-circles-areas-flat-vector-illustration_1284-72723.jpg?w=1480&amp;t=st=1672284259~exp=1672284859~hmac=a236fff8286951f71734499ee0c6acbf29ff7717268712e50fdcf7df8280cc7e 1480w, https://img.freepik.com/free-vector/skin-problems-infographics-scheme-with-fixing-pimples-black-heads-wrinkles-acne-allergy-dark-circles-areas-flat-vector-illustration_1284-72723.jpg?w=1800&amp;t=st=1672284259~exp=1672284859~hmac=a236fff8286951f71734499ee0c6acbf29ff7717268712e50fdcf7df8280cc7e 1800w, https://img.freepik.com/free-vector/skin-problems-infographics-scheme-with-fixing-pimples-black-heads-wrinkles-acne-allergy-dark-circles-areas-flat-vector-illustration_1284-72723.jpg?w=2000&amp;t=st=1672284259~exp=1672284859~hmac=a236fff8286951f71734499ee0c6acbf29ff7717268712e50fdcf7df8280cc7e 2000w" data-align="center"></p><h3>Overview</h3><p>With using Keras 2.2.4 and Tensorflow 1.11. Batch-Norm layer in this version of Keras is implemented in a way that: during training your network will always use the mini-batch statistics either the BN layer is frozen or not; also during inference you will use the previously learned statistics of the frozen BN layers. As a result, if you fine-tune the top layers, their weights will be adjusted to the mean/variance of the new dataset. Nevertheless, during inference they will receive data which are scaled differently because the mean/variance of the original dataset will be used. Consequently, if use Keras's example codes for fine-tuning Inception V3 or any network with batch norm layer, the results will be very bad. </p><h3>Need to know</h3><p>Import input skin image as:</p><p><br></p><p><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/37275b1d-fc75-41fd-9786-d81d9b9f84d9" width="276" height="183.44520482344174" style="display: block; margin: auto;" data-align="center"></p>

Skin Frequent Diseases With DenseNet

Frequent skin diseases classification from image with DenseNet 

<p><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/2efb5fb7-bf88-4918-b34c-1713300ecb7f"></p><h3><strong>Overview</strong></h3><p>Finds out symptoms similar to a given symptom, from a symptom-disease data set.</p><p>This model is used to predict symptoms that are closely related to a given sign. It can be used in cases (read apps) where the user enters a symptom. A list of similar symptoms pops up, of which the user can select the ones he's suffering from. These can be further fed into a model that can then predict the disease the person is suffering from, and redirect him to the associated specialist.</p><h3><strong>Need to know</strong></h3><p>You need to fill symptom to predict .</p><p><br></p>

Frequent Diseases Detection

Frequent diseases detection based on symtoms with Gradient Boosting


<h3><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/f777da83-d34b-45dc-9d17-7475d10b865b"></h3><h3><strong>Overview</strong></h3><p><span style="color: rgb(75, 79, 88);">Acne vulgaris remains one of the most common diseases afflicting humanity and it is the skin disease most commonly treated by physicians.&nbsp;It is a disease of the pilosebaceous units, clinically characterized by seborrhea, comedones, papules, pustules, nodules and, in some cases, scarring.&nbsp;Although easy to diagnose, the polymorphic nature of acne vulgaris and its varied extent of involvement do not permit simple evaluation of its severity. Because the acne lesions may vary in number during the natural course of the disease, various measurements have been developed, based on clinical examination and photographic documentation, to assess the clinical severity of acne vulgaris.&nbsp;Moreover, if the acne treatment regimens produced an all-or-none response, then acne measurements would be unnecessary.</span></p><h3><strong style="color: rgb(75, 79, 88);">Need to know</strong></h3><p class="ql-align-justify">The grading includes the following:</p><ul><li class="ql-align-justify"><strong>level 0 </strong>Simple non-inflammatory acne - comedones and a few papules.</li><li class="ql-align-justify"><strong>level 1 </strong>Comedones, papules and a few pustules.</li><li class="ql-align-justify"><strong>level 2 </strong>Larger inflammatory papules, pustules and a few cysts; a more severe form involving the face, neck and upper portions of the trunk.</li></ul><p class="ql-align-justify">You need import input image </p>

Acne Grading

<p><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/d99f3dda-2cd8-4175-af2b-2ab43f941199" width="375" height="375" style="display: block; margin: auto;" data-align="center"></p><p><br></p><h3><strong>Overview</strong></h3><p>Skin cancer continues to be the most frequently diagnosed with not only significant effects on health and well-being but also significant economic costs associated with treatment.&nbsp;A crucial step to the treatment and management of skin cancer is effective skin cancer detection due to strong prognosis when treated at an early stage, with one of the key screening approaches being dermoscopy examination.</p><h3><strong>Need to know</strong></h3><p>Import input is an image used to Skin Detection</p><p><br></p><p><br></p>

Skin Cancer

<p><img src="https://storage.googleapis.com/orailabelstudio/None/user_cc72cf3b-7cdf-444d-9205-5561b33ec7c8/604ac7b9-eaf6-4f37-9641-e91484a6db05"></p><h3><strong>Overview</strong></h3><p><span style="color: rgb(24, 24, 24);">The coronavirus disease 2019 (COVID-19) pandemic continues to have a tremendous impact on patients and healthcare systems around the world. In the fight against this novel disease, there is a pressing need for rapid and effective screening tools to identify patients infected with COVID-19, and to this end </span>Chest X-Ray<span style="color: rgb(24, 24, 24);"> imaging has been proposed as one of the key screening methods which may be used as a complement to RT-PCR testing, particularly in situations where patients undergo routine </span>Chest X-Ray<span style="color: rgb(24, 24, 24);"> scans for non-COVID-19 related reasons, patients have worsening respiratory status or developing complications that require expedited care, or patients are suspected to be COVID-19-positive but have negative RT-PCR test results. Early studies on </span>Chest X-Ray<span style="color: rgb(24, 24, 24);">-based screening have reported abnormalities in chest </span>Chest X-Ray<span style="color: rgb(24, 24, 24);"> images which are characteristic of COVID-19 infection, but these abnormalities may be difficult to distinguish from abnormalities caused by other lung conditions.</span></p><h3><strong style="color: rgb(24, 24, 24);">Need to know</strong></h3><p>You need to upload Chest X-Ray image to predict</p>

Pneumonia Prediction from Chest X-Ray Image

Pneumonia prediction from chest X-Ray image with CNN

<p><img class="thumb" fetchpriority="high" data-pin-no-hover="true" src="https://img.freepik.com/free-vector/person-suffering-from-rush_74855-6623.jpg?t=st=1672135613~exp=1672136213~hmac=8f61a74552cbb9d59450ee6daa989ebdd60fb0458d5c05a0498d639e4ba5cec1" sizes="(max-width: 479px) 100vw, (min-aspect-ratio: 626/417) calc((100vh - 184px) * 1.501199040767386), (max-width: 1095px) calc(100vw - 40px), calc(100vw - 540px)" width="369" height="245.80351437699682" alt="Free vector person suffering from rush" style="max-width: calc((100vh - 184px) * 1.5012); display: block; margin: auto;" srcset="https://img.freepik.com/free-vector/person-suffering-from-rush_74855-6623.jpg?w=360&amp;t=st=1672135618~exp=1672136218~hmac=d4f58ab975fe8b128c454797e6cc5fd632dffc1671a9a0b907e27fd353abfb37 360w, https://img.freepik.com/free-vector/person-suffering-from-rush_74855-6623.jpg?w=740&amp;t=st=1672135618~exp=1672136218~hmac=d4f58ab975fe8b128c454797e6cc5fd632dffc1671a9a0b907e27fd353abfb37 740w, https://img.freepik.com/free-vector/person-suffering-from-rush_74855-6623.jpg?w=826&amp;t=st=1672135618~exp=1672136218~hmac=d4f58ab975fe8b128c454797e6cc5fd632dffc1671a9a0b907e27fd353abfb37 826w, https://img.freepik.com/free-vector/person-suffering-from-rush_74855-6623.jpg?w=900&amp;t=st=1672135618~exp=1672136218~hmac=d4f58ab975fe8b128c454797e6cc5fd632dffc1671a9a0b907e27fd353abfb37 900w, https://img.freepik.com/free-vector/person-suffering-from-rush_74855-6623.jpg?w=996&amp;t=st=1672135618~exp=1672136218~hmac=d4f58ab975fe8b128c454797e6cc5fd632dffc1671a9a0b907e27fd353abfb37 996w, https://img.freepik.com/free-vector/person-suffering-from-rush_74855-6623.jpg?w=1060&amp;t=st=1672135618~exp=1672136218~hmac=d4f58ab975fe8b128c454797e6cc5fd632dffc1671a9a0b907e27fd353abfb37 1060w, https://img.freepik.com/free-vector/person-suffering-from-rush_74855-6623.jpg?w=1380&amp;t=st=1672135618~exp=1672136218~hmac=d4f58ab975fe8b128c454797e6cc5fd632dffc1671a9a0b907e27fd353abfb37 1380w, https://img.freepik.com/free-vector/person-suffering-from-rush_74855-6623.jpg?w=1480&amp;t=st=1672135618~exp=1672136218~hmac=d4f58ab975fe8b128c454797e6cc5fd632dffc1671a9a0b907e27fd353abfb37 1480w, https://img.freepik.com/free-vector/person-suffering-from-rush_74855-6623.jpg?w=1800&amp;t=st=1672135618~exp=1672136218~hmac=d4f58ab975fe8b128c454797e6cc5fd632dffc1671a9a0b907e27fd353abfb37 1800w, https://img.freepik.com/free-vector/person-suffering-from-rush_74855-6623.jpg?w=2000&amp;t=st=1672135618~exp=1672136218~hmac=d4f58ab975fe8b128c454797e6cc5fd632dffc1671a9a0b907e27fd353abfb37 2000w" data-align="center"></p><h3>Overview</h3><p>We always wanted to build an end to end ml solution - starting with model creation and ending with a live web app. Here we managed to do it. Users are able to submit a picture of a skin disease and get an instant prediction. It is a fine tuned MobileNet CNN. The main challenges were the unbalanced dataset and the small amount of data. We used data augmentation to reduce the class imbalance and in so doing get categorical accuracy scores that were not heavily skewed by a single majority class.</p><p>MobileNet’s small size and speed makes it ideal for web deployment. It’s also a joy to train.</p><h3>Need to know</h3><p>import input image as example:</p><p><a class="showcase__link js-detail-data-link" href="https://www.freepik.com/free-photo/person-having-skin-allergy-close-up_19672621.htm#query=disease%20skin&amp;position=11&amp;from_view=search&amp;track=sph" id="dtl-19672621" data-id="19672621" data-cache-id="11">
									<img class="landscape loaded" src="https://img.freepik.com/free-photo/person-having-skin-allergy-close-up_23-2149140492.jpg?size=626&amp;ext=jpg&amp;uid=R88766062&amp;ga=GA1.2.579944705.1672131719&amp;semt=sph" alt="Free photo person having a skin allergy close-up" data-src="https://img.freepik.com/free-photo/person-having-skin-allergy-close-up_23-2149140492.jpg?size=626&amp;ext=jpg&amp;uid=R88766062&amp;ga=GA1.2.579944705.1672131719&amp;semt=sph" width="260" height="172.77662037037038" style="cursor: nesw-resize;">
						</a></p><p><br></p><p><a class="showcase__link js-detail-data-link" href="https://www.freepik.com/free-photo/person-having-skin-allergy-close-up_19672621.htm#query=disease%20skin&amp;position=11&amp;from_view=search&amp;track=sph" data-id="19672621" data-cache-id="11">
			</a></p><p><br></p><p><a class="showcase__link js-detail-data-link" href="https://www.freepik.com/free-photo/person-having-skin-allergy-close-up_19672621.htm#query=disease%20skin&amp;position=11&amp;from_view=search&amp;track=sph" data-id="19672621" data-cache-id="11">
		</a></p>

Skin Frequent Diseases

Frequent skin diseases classification from image with MobileNet