Match!
arXiv: Computer Vision and Pattern Recognition
Papers
25100
Papers 19607
1 page of 1,961 pages (19.6k results)
Newest
#1Hazrat Ali (CUI: COMSATS Institute of Information Technology)H-Index: 6
#2Ahsan Ullah (CUI: COMSATS Institute of Information Technology)
Last.Shahid Khattak (CUI: COMSATS Institute of Information Technology)H-Index: 8
view all 4 authors...
Automatic recognition of Urdu handwritten digits and characters, is a challenging task. It has applications in postal address reading, bank's cheque processing, and digitization and preservation of handwritten manuscripts from old ages. While there exists a significant work for automatic recognition of handwritten English characters and other major languages of the world, the work done for Urdu lan-guage is extremely insufficient. This paper has two goals. Firstly, we introduce a pioneer dataset...
Source
Artificial intelligence (AI) has been a topic of major research for many years. Especially, with the emergence of deep neural network (DNN), these studies have been tremendously successful. Today machines are capable of making faster, more accurate decision than human. Thanks to the great development of machine learning (ML) techniques, ML have been used many different fields such as education, medicine, malware detection, autonomous car etc. In spite of having this degree of interest and much s...
For intelligent vehicles, sensing the 3D environment is the first but crucial step. In this paper, we build a real-time advanced driver assistance system based on a low-power mobile platform. The system is a real-time multi-scheme integrated innovation system, which combines stereo matching algorithm with machine learning based obstacle detection approach and takes advantage of the distributed computing technology of a mobile platform with GPU and CPUs. First of all, a multi-scale fast MPV (Mult...
#2Shanmuganathan Raman (IITGN: Indian Institute of Technology Gandhinagar)H-Index: 8
In this paper, we propose a new convolutional layer called Depthwise-STFT Separable layer that can serve as an alternative to the standard depthwise separable convolutional layer. The construction of the proposed layer is inspired by the fact that the Fourier coefficients can accurately represent important features such as edges in an image. It utilizes the Fourier coefficients computed (channelwise) in the 2D local neighborhood (e.g., 3x3) of each position of the input map to obtain the feature...
#1Sadaf Gulshad (UvA: University of Amsterdam)H-Index: 1
#2Arnold W. M. Smeulders (UvA: University of Amsterdam)H-Index: 52
In this paper, we aim to explain the decisions of neural networks by utilizing multimodal information. That is counter-intuitive attributes and counter visual examples which appear when perturbed samples are introduced. Different from previous work on interpreting decisions using saliency maps, text, or visual patches we propose to use attributes and counter-attributes, and examples and counter-examples as part of the visual explanations. When humans explain visual decisions they tend to do so b...
Nowadays, full face synthesis and partial face manipulation by virtue of the generative adversarial networks (GANs) have raised wide public concern. In the digital media forensics area, detecting and ultimately locating the image forgery have become imperative. Although many methods focus on fake detection, only a few put emphasis on the localization of the fake regions. Through analyzing the imperfection in the upsampling procedures of the GAN-based methods and recasting the fake localization p...
#1Jie ChenH-Index: 1
Last.Haifeng Li (CSU: Central South University)H-Index: 9
view all 8 authors...
Remote sensing image scene classification is a fundamental but challenging task in understanding remote sensing images. Recently, deep learning-based methods, especially convolutional neural network-based (CNN-based) methods have shown enormous potential to understand remote sensing images. CNN-based methods meet with success by utilizing features learned from data rather than features designed manually. The feature-learning procedure of CNN largely depends on the architecture of CNN. However, m...
#1Jonathan Munro (UoB: University of Bristol)H-Index: 2
#2Dima Damen (UoB: University of Bristol)H-Index: 17
Fine-grained action recognition datasets exhibit environmental bias, where multiple video sequences are captured from a limited number of environments. Training a model in one environment and deploying in another results in a drop in performance due to an unavoidable domain shift. Unsupervised Domain Adaptation (UDA) approaches have frequently utilised adversarial training between the source and target domains. However, these approaches have not explored the multi-modal nature of video within ea...
In this work, we present a novel unsupervised image registration algorithm. It is differentiable end-to-end and can be used for both multi-modal and mono-modal registration. This is done using mutual information (MI) as a metric. The novelty here is that rather than using traditional ways of approximating MI, we use a neural estimator called MINE and supplement it with matrix exponential for transformation matrix computation. This leads to improved results as compared to the standard algorithms ...
Crowd scene analysis receives growing attention due to its wide applications. Grasping the accurate crowd location (rather than merely crowd count) is important for spatially identifying high-risk regions in congested scenes. In this paper, we propose a Compressed Sensing based Output Encoding (CSOE) scheme, which casts detecting pixel coordinates of small objects into a task of signal regression in encoding signal space. CSOE helps to boost localization performance in circumstances where target...
12345678910
Top fields of study
Machine learning
Pattern recognition
Computer science
Artificial neural network
Convolutional neural network
Segmentation