Search · four archives
Search · four archives
21 papers · ranked by Valyu relevance
Abrar Ahmed, Ahmad Jalal, Kibum Kim
In recent years, interest in scene classification of different indoor-outdoor scene images has increased due to major developments in visual sensor techniques. Scene classification has been demonstrated to be an efficient method for environmental observations but it is a challenging task considering the complexity of…
Salman Khan, Munawar Hayat, Mohammed Bennamoun, Roberto Togneri + 1 more
'Ferdous Sohel'] Abstract—Indoor scene recognition is a multi-faceted and challenging problem due to the diverse intra-class variations and the confusing inter-class similarities. This paper presents a novel approach which exploits rich mid-level convolutional features to categorize indoor scenes. Traditionally used…
Ashraf Sadat Jabari, Mohammad Reza Keyvanpour
Scene mining is a subset of image mining in which scenes are classified to a distinct set of classes based on analysis of their content. In other word in scene mining, a label is given to visual content of scene, for example, mountain, beach. Scene mining is used in applications such as medicine, movie, information…
Lu Liu
On the basis of scene visual understanding technology, the research aims to further improve the classification efficiency and classification accuracy of art design scenes. The lightweight deep learning (DL) model based on big data is used as the main method to achieve real-time detection and recognition of multiple…
Hafeez Ur Rehman Siddiqui, Adil Ali Saleem, Muhammad Amjad Raza, Kainat Zafar + 4 more
'Kainat Zafar' 'Riccardo Russo' 'Sandra Dudley' 'Mario Munoz-Organero' 'Ki H. Chon'] Noisy environments, changes and variations in the volume of speech, and non-face-to-face conversations impair the user experience with hearing aids. Generally, a hearing aid amplifies sounds so that a hearing-impaired person can…
Taiki Orima, Fumiya Kurosawa, Taisei Sekimoto, Isamu Motoyoshi
Recent studies have suggested the importance of statistical image features in both natural scene and object recognition, while the spatial layout or shape information is still important. In the present study, to investigate the roles of low- and high-level statistical image features in natural scene and object…
Kexin Liu, Rong Wang, Xiaoou Song, Xiaobing Deng + 2 more
'Qiangqiang Yuan'] Currently, complex scene classification strategies are limited to high-definition image scene sets, and low-quality scene sets are overlooked. Although a few studies have focused on artificially noisy images or specific image sets, none have involved actual low-resolution scene images. Therefore…
Ligang Zhang
Scene parsing aims to recognize the object category of every pixel in scene images, and it plays a central role in image content understanding and computer vision applications. However, accurate scene parsing from unconstrained real-world data is still a challenging task. In this paper, we present the non-parametric…
Ting Wang, Xiao Yan, Jiawei Li, Xilong Luo + 1 more
The extraction, classification, and judgment of sports video scenes can improve work efficiency and accuracy. To understand sports videos in dynamic scenes, this study applies deep learning technology, firstly introducing clustering algorithm and attention mechanism to improve the target detection technology You Only…
O. Leon Barbed, Pablo Azagra, Juan Plo, Ana C. Murillo
Purpose We aim to automate the initial analysis of complete endoscopy videos, identifying the sparse relevant content. This facilitates long procedure recording understanding, reduces the clinicians’ review time, and facilitates downstream tasks such as video summarization, event detection, and 3D reconstruction.…
Amirhossein Aminimehr, Amirali Molaei, Erik Cambria
Scene recognition based on deep-learning has made significant progress, but there are still limitations in its performance due to challenges posed by inter-class similarities and intra-class dissimilarities. Furthermore, prior research has primarily focused on improving classification accuracy, yet it has given less…
Huy Phan, Lars Hertel, Marco Maaß, Philipp Koch + 1 more
We present in this paper an efficient approach for acoustic scene classification by exploring the structure of class labels. Given a set of class labels, a category taxonomy is automatically learned by collectively optimizing a clustering of the labels into multiple meta-classes in a tree structure. An acoustic scene…
Kayo Nada, Keisuke Imoto, Takao Tsuchiya
Acoustic scene classification (ASC) and sound event detection (SED) are major topics in environmental sound analysis. Considering that acoustic scenes and sound events are closely related to each other, the joint analysis of acoustic scenes and sound events using multitask learning (MTL)-based neural networks was…
Ivan Sikirić, Karla Brkić, Siniša Šegvić
—This paper investigates classification of traffic scenes in a very low bandwidth scenario, where an image should be coded by a small number of features. We introduce a novel dataset, called the FM1 dataset, consisting of 5615 images of eight different traffic scenes: open highway, open road, settlement, tunnel, tunnel…
Raphaël Marée, Pierre Geurts, Louis Wehenkel
Background With the improvements in biosensors and high-throughput image acquisition technologies, life science laboratories are able to perform an increasing number of experiments that involve the generation of a large amount of images at different imaging modalities/scales. It stresses the need for computer vision…
Hanna Böhner, Eivind Flittie Kleiven, Rolf Anker Ims, Eeva M. Soininen
Camera traps have become popular for monitoring biodiversity and animal populations. Artificial intelligence is increasingly used to automatically classify large image data sets produced by camera traps and many tools that incorporate machine-learning models for automatic image classification have been developed over…
Pedro Villar, Jacobo Casado, David Fernández, Pedro Sánchez + 1 more
Diatoms are microscopic organisms belonging to the algae kingdom. They adapt to the ecosystem and modify their shape and texture depending on hundreds of ecosystem variables. Hence, these micro-organism are considered as the most accurate indicator to measure water quality. Commonly, the recognition of the class of…
Arnold Wiliem, Conrad Sanderson, Yongkang Wong, Peter Hobson + 2 more
This paper describes a novel system for automatic classification of images obtained from Anti-Nuclear Antibody (ANA) pathology tests on Human Epithelial type 2 (HEp-2) cells using the Indirect Immunofluorescence (IIF) protocol. The IIF protocol on HEp-2 cells has been the hallmark method to identify the presence of…
Authors not listed
In experimental chemistry, actions are adjusted based on what we see—such as dosing until dissolution, heating until melting, or stirring until mixing is complete. However, current self-driving labs (SDLs) do not monitor these visual cues. HeinSight 4.0 fills this gap by integrating computer vision into SDLs to enable…
Hang Hu, Jyothsna Padmakumar Bindu, Julia Laskin
Mass spectrometry imaging (MSI) is widely used for the label-free molecular mapping of biological samples. The identification of co-localized molecules in MSI data is crucial to the understanding of biochemical pathways. However, complex MSI data are too large for manual annotation but too small for training deep…
Yoshikazu Matsuoka, Kevin A. Brown, Ryusuke Nakatsuka, Tatsuya Fujioka
Morphological images of cells contain extensive information, which help biologists to infer the type and state of cells to some degree based on their morphology. Convolutional Neural Network, a neural network architecture, is a powerful tool used for image recognition. However, whether it can be used to classify cells…