Machine Learning
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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These are the coefficients of the equivalent velocity increment estimator for minimum-time low-thrust transfers to the geostationary orbit.
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This dataset contains raw captured packet headers from six commercial drones.
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1026 Views
Question Answer Pair dataset for Sentiment Analysis Tasks.
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Non uniformly illuminated Blender simulated and camera captured haze masks.
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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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For whole-testis cross-section analysis the output predictions from 1024x1024 images were merged and the whole-testis cross-section image was recompiled, with the annotated cellular and tubular objects, which were derived from cell and tubule models, respectively . This figure provides a high-resolution image of whole-testis cross-section analysis with cellular and tubular labels.
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We can create ANN-based and SVM-based flip-flop timing models with the help of SPICE simulations. This dataset contains training/test samples obtained using SPICE simulation for creating/testing these ML-based models.
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The C3I Synthetic Human Dataset provides 48 female and 84 male synthetic 3D humans in fbx format generated from iClone 7 Character creator “Realistic Human 100” toolkit with variations in ethnicity, gender, race, age, and clothing. For each of these, it further provides the full-body model with five different facial expressions – Neutral, Angry, Sad, Happy, and Scared. Along with the body models, it also open-sources a data generation pipeline written in python to bring those models into a 3D Computer Graphics tool called Blender.
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655 Views