object detection
This database contains Synthetic High-Voltage Power Line Insulator Images.
There are two sets of images: one for image segmentation and another for image classification.
The first set contains images with different types of materials and landscapes, including the following landscape types: Mountains, Forest, Desert, City, Stream, Plantation. Each of the above-mentioned landscape types consists of 2,627 images per insulator type, which can be Ceramic, Polymeric or made of Glass, with a total of 47,286 distinct images.
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424 Views
DIRS24.v1 presents a dataset captured in campus environment. These images are curated suitably for the utilization in developing perception modules. These modules can be very well employed in Advanced Driver Assistance Systems (ADAS). The images of dataset are annotated in diversified formats such as COCO-MMDetection, Pascal-VOC, TensorFlow, YOLOv7-PyTorch, YOLOv8-Oriented Bounding Box, and YOLOv9.
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409 Views
This paper presents a deep learning model for fast and accurate radar detection and pixel-level localization of large concealed metallic weapons on pedestrians walking along a sidewalk. The considered radar is stationary, with a multi-beam antenna operating at 30 GHz with 6 GHz bandwidth. A large modeled data set has been generated by running 2155 2D-FDFD simulations of torso cross sections of persons walking toward the radar in various scenarios.
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3 Views
The steel tube dataset comprises comprehensive information on various attributes related to steel tubes, encompassing dimensions, material composition, manufacturing processes, and performance characteristics. This dataset facilitates in-depth analysis of steel tube properties, aiding researchers, engineers, and industry professionals in optimizing designs, ensuring structural integrity, and advancing materials science in the context of steel tube applications.
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320 Views
This dataset, referred to as LIED (Light Interference Event Dataset), is showcased in the article titled 'Identifying Light Interference in Event-Based Vision'. We proposed the LIED, it has three categories of light interference, including strobe light sources, non-strobe light sources and scattered or reflected light. Moreover, to make the datasets contain more realistic scenarios, the datasets include the dynamic objects and the situation of camera static and the camera moving. LIED was recorded by the DAVIS346 sensor. It provides both frame and events with the resolution of 346 * 260.
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83 Views
Deficient domestic wastewater management, industrial waste, and floating debris are some leading factors that contribute to inland water pollution. The surplus of minerals and nutrients in overly contaminated zones can lead to the invasion of different invasive weeds. Lemnaceae, commonly known as duckweed, is a family of floating plants that has no leaves or stems and forms dense colonies with a fast growth rate. If not controlled, duckweed establishes a green layer on the surface and depletes fish and other organisms of oxygen and sunlight.
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104 Views
Just Recognizable Distortion (JRD) refers to the minimum distortion that notably affects the recognition performance of a machine vision model. If a distortion added to images or videos falls within this JRD threshold, the degradation of the recognition performance will be unnoticeable. Based on this JRD property, it will be useful to Video Coding for Machine (VCM) to minimize the bit rate while maintaining the recognition performance of compressed images.
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370 Views
To enable intelligent vehicles and transportation systems, the vehicles and relevant systems need to have the ability to sense environment and recognize objects. In order to benefit from the robustness of radar for sensing, knowing how to use the radar system for effective object recognition is critical. Observing this, we in this paper propose a novel deep learning-aided object recognition system for radar systems by combining the You only look once (YOLO) system with a proposed object recheck system.
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141 Views
In this dataset, we provided the raw analog-to-digital-converter (ADC) data of a 77GHz mmwave radar for the automotive object detection scenario. The overall dataset contains approximately 19800 frames of radar data as well as synchronized camera images and labels. For each radar frame, its raw data has 4 dimension: samples (fast time), chirps (slow time), transmitters, receivers. The experiment radar was assembled from the TI AWR 1843 board, with 2 horizontal transmit antennas and 4 receive antennas.
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5239 Views
This dataset has a collection of 383 raw images of Indian vehicles in different illumination conditions using Infrared Day/Night Camera. The dataset resembles the Indian highway toll collection plazas. The dataset will be useful in developing intelligent models for applications such as automated toll collection, number plate detection and recognition, driverless vehicles, suspicious vehicle traction, and traffic management.
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2447 Views