Results 101 to 110 of about 3,462,291 (207)

Transformer‐Based Contextual Modeling for Predicting Calories From Recipes

Applied AI Letters, Volume 7, Issue 3, October 2026.
A transformer‐based regression model with token‐level attention pooling is proposed for predicting calorie content directly from unstructured recipe text. By fine‐tuning RoBERTa in an end‐to‐end manner, attention is learned to be focused on calorie‐relevant tokens such as ingredients, fats, and cooking methods.
Md. Siam Ansary, Amina Brinto
wiley   +1 more source

The Fourth Monocular Depth Estimation Challenge

2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
To appear in ...
Anton Obukhov, Matteo Poggi, Fabio Tosi, Ripudaman Singh Arora, Jaime Spencer, Chris Russell 0001, Simon Hadfield, Richard Bowden, Shuaihang Wang, Zhenxin Ma, Weijie Chen 0006, Baobei Xu, Fengyu Sun, Di Xie, Jiang Zhu, Mykola Lavreniuk, Haining Guan, Qun Wu, Yupei Zeng, Chao Lu, Huanran Wang, GuangYuan Zhou, Haotian Zhang, Jianxiong Wang, Qiang Rao, Chunjie Wang, Xiao Liu 0004, Zhiqiang Lou, Hualie Jiang, Yihao Chen, Rui Xu, Minglang Tan, Zihan Qin, Yifan Mao, Jiayang Liu, Jialei Xu, Yifan Yang 0007, Wenbo Zhao 0004, Junjun Jiang, Xianming Liu 0005, Mingshuai Zhao, Anlong Ming, Wu Chen, Feng Xue 0001, Mengying Yu, Shida Gao, Xiangfeng Wang 0007, Gbenga Omotara, Ramy Farag, Jacket Demby's, Seyed Mohamad Ali Tousi, Guilherme N. DeSouza, Tuan-Anh Yang, Minh-Quang Nguyen, Thien-Phuc Tran, Albert Luginov, Muhammad Shahzad   +56 more
openaire   +4 more sources

Transferable Deep Reinforcement Learning With Edge‐Contour‐Depth Fusion for Autonomous Wireless Capsule Endoscopy Navigation

Advanced Science, Volume 13, Issue 49, 3 September 2026.
This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu, Haitao Gao, Qingyang Liu, Sishen Yuan, Haiyang Fang, Mingwu Su, Baijia Liang, Yongzun Yang, Long Bai, Wenzhen Dong, Dihong Xie, Shijian Su, Jiewen Lai, Shing Shin Cheng, Zhen Li, Xiuli Zuo, Hongliang Ren   +16 more
wiley   +1 more source

Monocular Depth Estimation: A Thorough Review

IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of depth in two-dimensional images is among the challenging topics in Computer Vision. This is a well-studied but also an ill-posed problem, which has long been the focus of intense research. This paper is an in-depth review of the topic, presenting two aspects, one that considers the mechanisms of human depth perception, and another that ...
Arampatzakis, Vasileios, Pavlidis, George, Mitianoudis, Nikolaos, Papamarkos, Nikos   +3 more
openaire   +4 more sources

Depth estimation for a road scene using a monocular image sequence based on fully convolutional neural network

International Journal of Advanced Robotic Systems, 2020
An advanced driving assistant system is one of the most popular topics nowadays, and depth estimation is an important cue for advanced driving assistant system.
Haixia Wang, Yehao Sun, Zhiguo Zhang, Xiao Lu, Chunyang Sheng   +4 more
doaj   +1 more source

Bionic Tactile Skins for Robotics: Fundamentals, Advances, and Future Prospects

SmartSys, Volume 2, Issue 3, September 2026.
ABSTRACT Robotic bionic tactile skins (RBTSs), as crucial components of next‐generation robotic systems, have attracted significant attention in recent years. By enabling robots to achieve human‐like tactile perception and interact effectively with their surroundings, RBTSs play an essential role in enhancing robotic intelligence.
Jiajun Wu, Zitong Zhang, Xuhui Zhou, Yu Meng, Jie Ni, Junshan Liu, Faheng Zang, Xiaojun Guo, Zhuoqing Yang   +8 more
wiley   +1 more source

The Third Monocular Depth Estimation Challenge

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
To appear in ...
Jaime Spencer, Fabio Tosi, Matteo Poggi, Ripudaman Singh Arora, Chris Russell 0001, Simon Hadfield, Richard Bowden, GuangYuan Zhou, ZhengXin Li, Qiang Rao, YiPing Bao, Xiao Liu 0004, Dohyeong Kim, Jinseong Kim, Myunghyun Kim, Mykola Lavreniuk, Rui Li 0013, Qing Mao, Jiang Wu, Yu Zhu 0004, Jinqiu Sun, Yanning Zhang 0001, Suraj Patni, Aradhye Agarwal, Chetan Arora 0002, Pihai Sun, Kui Jiang, Gang Wu 0010, Jian Liu 0036, Xianming Liu 0005, Junjun Jiang, Xidan Zhang, Jianing Wei, Fangjun Wang, Zhiming Tan, Jiabao Wang, Albert Luginov, Muhammad Shahzad, Seyed Hosseini, Aleksander Trajcevski, James H. Elder   +40 more
openaire   +4 more sources

Using Drones for Large Mammal Monitoring

Mammal Review, Volume 56, Issue 3, September 2026.
Drones were used to obtain video data on animals and locations and distance from the midline was automatically determined by our pipeline so that the input for Distance sampling is generated. ABSTRACT Introduction The emergence of drones has profoundly transformed the field of large mammal monitoring, offering unprecedented capabilities for data ...
Chaim Chai Elchik, Michael Hudson, Sam Buckland, Steven Longmore, Serge Wich   +4 more
wiley   +1 more source

Monocular Depth Estimation for Autonomous Driving

, 2022
Universitat Autònoma de Barcelona.
openaire   +2 more sources

Accurate depth from defocus estimation with video-rate implementation [PDF]

The science of measuring depth from images at video rate using „defocus‟ has been investigated. The method required two differently focussed images acquired from a single view point using a single camera.
Raj, Alex Noel Joseph
core