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Wenbo Peng and Jinjie Huang
Current object detection methods typically focus on addressing the distribution discrepancies between source and target domains. However, solely concentrating on this aspect may lead to overlooking the inherent limitations of the samples themselves. This...
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Kavitha Srinivasan, Sainath Prasanna, Rohit Midha, Shraddhaa Mohan
Pág. 1 - 20
Advances have been made in the field of Machine Learning showing that it is an effective tool that can be used for solving real world problems. This success is hugely attributed to the availability of accessible data which is not the case for many fields...
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Shengyu Zhang, Zhencai Zhu, Haiying Hu and Yuqing Li
Aiming at the task planning and scheduling problem of space object detection LEO constellation (SODLC) for detecting space objects in deep space background, a method of SODLC task satellite selection based on observation window projection analysis is pro...
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Shuai Dong, Wei Wang, Wensheng Li and Kun Zou
A 2D floor plan (FP) often contains structural, decorative, and functional elements and annotations. Vectorization of floor plans (VFP) is an object detection task that involves the localization and recognition of different structural primitives in 2D FP...
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Niranjan Ravi and Mohamed El-Sharkawy
Three-dimensional object detection involves estimating the dimensions, orientations, and locations of 3D bounding boxes. Intersection of Union (IoU) loss measures the overlap between predicted 3D box and ground truth 3D bounding boxes. The localization t...
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Dippal Israni,Hiren Mewada
Pág. 290 - 301
Identity assignment and retention needs multiple object detection and tracking. It plays a vital role in behavior analysis and gait recognition. The objective of Multiple Object Tracking (MOT) is to detect, track and retain identities from an image seque...
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Michal Tomaszewski, Pawel Michalski and Jakub Osuchowski
This article presents an analysis of the effectiveness of object detection in digital images with the application of a limited quantity of input. The possibility of using a limited set of learning data was achieved by developing a detailed scenario of th...
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Jiahao Li, Ronja Güldenring and Lazaros Nalpantidis
Autonomous weeding robots need to accurately detect the joint stem of grassland weeds in order to control those weeds in an effective and energy-efficient manner. In this work, keypoints on joint stems and bounding boxes around weeds in grasslands are de...
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Marios Mamalis, Evangelos Kalampokis, Ilias Kalfas and Konstantinos Tarabanis
The verticillium fungus has become a widespread threat to olive fields around the world in recent years. The accurate and early detection of the disease at scale could support solving the problem. In this paper, we use the YOLO version 5 model to detect ...
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Xinzhi Liu, Jun Yu, Toru Kurihara, Congzhong Wu, Zhao Niu and Shu Zhan
It seems difficult to recognize an object from its background with similar color using conventional segmentation methods. An efficient way is to utilize hyperspectral images that contain more wave bands and richer information than only RGB components. Pa...
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Jian Ni, Rui Wang and Jing Tang
The detection of small objects is easily affected by background information, and a lack of context information makes detection difficult. Therefore, small object detection has become an extremely challenging task. Based on the above problems, we proposed...
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Daniel Rocha, Filomena Soares, Eva Oliveira and Vítor Carvalho
The ways in which people dress, as well as the styles that they prefer for different contexts and occasions, are part of their identity. Every day, blind people face limitations in identifying and inspecting their garments, and dressing can be a difficul...
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Chunxian Wang, Xiaoxing Wang, Yiwen Wang, Shengchao Hu, Hongyang Chen, Xuehai Gu, Junchi Yan and Tao He
Neural architecture search (NAS) is a popular branch of automatic machine learning (AutoML), which aims to search for efficient network structures. Many prior works have explored a wide range of search algorithms for classification tasks, and have achiev...
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Qian Zhang, Jie Ren, Hong Liang, Ying Yang and Lu Chen
Small object detection becomes a challenging problem in computer vision due to low resolution and less feature information. Making full use of high-resolution features is an important factor in improving small object detection. In this paper, to improve ...
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Florin Dumitrescu, Bogdan Ceachi, Ciprian-Octavian Truica, Mihai Trascau and Adina Magda Florea
Space Surveillance and Tracking is a task that requires the development of systems that can accurately discriminate between natural and man-made objects that orbit around Earth. To manage the discrimination between these objects, it is required to analyz...
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Sergey Golubev, Evgenia Novikova and Elena Fedorchenko
Recently, approaches based on the transformation of tabular data into images have gained a lot of scientific attention. This is explained by the fact that convolutional neural networks (CNNs) have shown good results in computer vision and other image-bas...
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Priyank Kalgaonkar and Mohamed El-Sharkawy
Object detection is a computer vision task of detecting instances of objects of a certain class, identifying types of objects, determining its location, and accurately labelling them in an input image or a video. The scope of the work presented within th...
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Fidel Aznar, Mar Pujol and Ramón Rizo
This article presents a macroscopic swarm foraging behavior obtained using deep reinforcement learning. The selected behavior is a complex task in which a group of simple agents must be directed towards an object to move it to a target position without t...
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Jang You Park, Dong June Ryu, Kwang Woo Nam, Insung Jang, Minseok Jang and Yonsik Lee
Density-based clustering algorithms have been the most commonly used algorithms for discovering regions and points of interest in cities using global positioning system (GPS) information in geo-tagged photos. However, users sometimes find more specific a...
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Han Fu, Xiangtao Fan, Zhenzhen Yan and Xiaoping Du
The detection of primary and secondary schools (PSSs) is a meaningful task for composite object detection in remote sensing images (RSIs). As a typical composite object in RSIs, PSSs have diverse appearances with complex backgrounds, which makes it diffi...
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