Machine Learning
Accurate fire load (combustible objects) information is crucial for safety design and resilience assessment of buildings. Traditional fire load acquisition methods, such as fire load survey, which are time-consuming, tedious, and error-prone, failed to adapt to dynamic changed indoor scenes. As a starting point of automatic fire load estimation, fast recognition and detection of indoor fire load are important. Thus, A dataset containing images of indoor scenes and annotations of instance segmentation is developed in this research.
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1589 Views
The EegDot data set (EEG data evoked by Different Odor Types established by Tianjin University) collected using a Cerebus neural signal acquisition equipment involved thirteen odor stimulating materials, five of which (smelling like rose (A), caramel (B), rotten (C), canned peach (D), and excrement (E)) were selected from the T&T olfactometer (from the Daiichi Yakuhin Sangyo Co., Ltd., Japan) and the remaining eight from essential oils (i.e., mint (F), tea tree (G), coffee (H), rosemary (I), jasmine (J), lemon (K), vanilla (L) and lavender (M)).
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1304 Views
The C3I Synthetic Face Depth Dataset consists of 3D virtual human models and 2D rendered RGB and GT depth images in zipped version into two folders for male and female.
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1733 Views
Technical question-answering sites like Stack Overflow are gaining enormous attention from the practitioners of specialized fields to exchange their programming knowledge. They ask questions on different topics, having various levels of difficulty and complexity. To answer such questions, all practitioners do not have the same level of expertise on those topics. However, the existing approach of Stack Overflow does not consider the difficulty and primarily filters out the questions based on topics only.
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200 Views
Nowadays, with the rapid increase in the number of applications and networks, the number of cyber multi-step attacks has been increasing exponentially. Thus, the need for a reliable and acceptable Intrusion Detection System (IDS) solution is becoming urgent to protect the networks and devices. However, implementing a robust IDS needs a reliable and up-to-date dataset in order to capture the behaviors of the new types of attacks, especially multi-step attacks. In this work, a new benchmark Multi-Step Cyber-Attack Dataset (MSCAD) is introduced.
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3156 Views
KSU-ArSL was developed by the Center of Smart Robotics Research at King Saud University (KSU) in conjunction with the Higher Education Program for the Deaf and Hard of Hearing. The dataset consists of 80 classes (belonging to 80 signs) recorded by 40 healthy subjects using three cameras (one RGB and two Microsoft Kinect cameras). Each subject repeated each sign 5 times in five separate sessions at the same day. As a result, there are 200 video samples per class, 16000 samples in total per camera.
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1830 Views
We created a 2563-image custom dragon fruit image dataset, with 1248 images of raw dragon fruits and 1315 photographs of ripe dragon fruits. The images were taken with the Nikon D5200 DSLR and OnePlus 6's Sony IMX 519 16 megapixel camera. The photographs taken with the DSLR camera had a resolution of 4000 by 6000 pixels, while those taken with the OnePlus6 had a resolution of 3456 by 4608 pixels. They were photographed in natural sunlight. The average temperature during that time was 28°C (84.2°F), with partly sunny skies, 65 percent humidity, and 17 km/h wind speeds.
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2833 Views
We present an improved EfficientDet network module , accomplished by adding attention mechanism, deformable convolution, and multiclass focal loss. The image shows the flowchart of proposed approach.
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23 Views
Contrast-enhanced computed tomography (CE-CT) is the gold standard for diagnosing AD. However, contrast agents can cause allergic reactions or renal failure in some patients. Moreover, AD diagnosis by radiologists using non- contrast-enhanced CT (NCE-CT) images has poor sensitivity. To address this issue, a novel deep learning methos was proposed for AD detection using NCE-CT volumes. It may have great potential to reduce the misdiagnosis of AD using NCE-CT in clinical practice.
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283 Views
It presents bigest Assamese Isolated handwritten numeral dataset that is consist of 35106 numerals samples in grayscale format of uniform size 28x28. The contributors arestudents and Academic professionals.
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160 Views