Machine Learning
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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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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276 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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146 Views
This dataset is used for the identification of video in the internet traffic. The dataset was prepared by using Wireshark. It comprises of two types of traffic data, VPN (Virtual Private Network) or encrypted traffic data and Non-VPN or unencrypted traffic. The dataset consist of the data streams (.pcap) of 43 videos. Each video is played 50 times in both VPN and Non-VPN mode. The streams were obtained by setting-up a dummy client on a PC which plays a YouTube video and Wireshark is used to capture the internet traffic.
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1849 Views
These are the coefficients of the equivalent velocity increment estimator for minimum-time low-thrust transfers to the geostationary orbit.
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74 Views
This dataset contains raw captured packet headers from six commercial drones.
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991 Views
Question Answer Pair dataset for Sentiment Analysis Tasks.
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98 Views
Non uniformly illuminated Blender simulated and camera captured haze masks.
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69 Views
The following folder contains the data simulated using the metholodgy described in the paper titled "Federated Learning based Base Station Selection using LiDAR Data"
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Data of cricket bowlers was recorded using wearable IMU sensors. Data were collected from the designed sensor units placed on the thigh and tibia of the front leg of each bowler using a strap. Recorded data include 3-axes accelerometer data and 4-dimensional quaternion data.
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