28 papers · ranked by Valyu relevance
Seiichi Uchida
This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the…
Tomochika Fujisawa, Víctor Noguerales, Emmanouil Meramveliotakis, Anna Papadopoulou + 1 more
Complex bulk samples of invertebrates from biodiversity surveys present a great challenge for taxonomic identification, especially if obtained from unexplored ecosystems. High-throughput imaging combined with machine learning for rapid classification could overcome this bottleneck. Developing such procedures requires…
Hiliwi Leake Kidane
Classification of Visual Object Classes represents one of the most elaborated areas of interest in Computer Vision. It is always challenging to get one specific detector, descriptor or classifier that provides the expected object classification result. Consequently, it critical to compare the different detection…
Quyet-Tien Le, Patricia Ladret, Huu-Tuan Nguyen, Alice Caplier
The main goal of this paper is to study Image Aesthetic Assessment (IAA) indicating images as high or low aesthetic. The main contributions concern three points. Firstly, following the idea that photos in different categories (human, flower, animal, landscape, …) are taken with different photographic rules, image…
Nouna Khandan
Digitization, i.e., the process of converting information into a digital format, may provide various opportunities (e.g., increase in productivity, disaster recovery, and environmentally friendly solutions) and challenges for businesses. In this context, one of the main challenges would be to accurately classify…
Bekhzod Olimov, Barathi Subramanian, Rakhmonov Akhrorjon Akhmadjon Ugli, Jea-Soo Kim + 1 more
'Rakhmonov Akhrorjon Akhmadjon Ugli' 'Jea-Soo Kim' 'Jeonghong Kim'] Extracting useful features at multiple scales is a crucial task in computer vision. The emergence of deep-learning techniques and the advancements in convolutional neural networks (CNNs) have facilitated effective multiscale feature extraction that…
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…
Kohulan Rajan, Henning Otto Brinkhaus, M. Isabel Agea, Achim Zielesny + 1 more
The number of publications describing chemical structures has increased steadily over the last decades. However, the majority of published chemical information is currently not available in machine-readable form in public databases. It remains a challenge to automate the process of information extraction in a way that…
Serrano Pereira, Barbara Gravendeel, Patrick Wijntjes, Rutger A. Vos
Taxonomic expertise for the identification of species is rare and costly. On-going advances in computer vision and machine learning have led to the development of numerous semi- and fully automated species identification systems. However, these systems are rarely agnostic to specific morphology, rarely can perform…
Alessandro Bruno
A growing number of commercially available mobile phones come with integrated high-resolution digital cameras. That enables a new class of dedicated applications to image analysis such as mobile visual search, image cropping, object detection, content-based image retrieval, image classification. In this paper, a new…
Abhishek Pandey, Anjna Jayant Deen, Rajeev Pandey
The improvement of the accuracy of image query retrieval used image classification technique. Image classification is well known technique of supervised learning. The improved method of image classification increases the working efficiency of image query retrieval. For the improvements of classification technique we…
Yazhou Yao, Jian Zhang, Fumin Shen, Xian‐Sheng Hua + 2 more
'Zhenmin Tang'] Abstract—Studies show that refining real-world categories into semantic subcategories contributes to better image modeling and classification. Previous image sub-categorization work relying on labeled images and WordNet's hierarchy is not only laborintensive, but also restricted to classify images into…
Maminiaina Alphonse Rafidison, Hajasoa Malalatiana Ramafiarisona, Paul Auguste Randriamitantsoa, Sabine Harisoa Jacques Rafanantenana + 3 more
'Paul Auguste Randriamitantsoa' 'Sabine Harisoa Jacques Rafanantenana' 'Faniriharisoa Maxime Rajaonarison Toky' 'Lovasoa Patrick Rakotondrazaka' 'Andry Harivony Rakotomihamina'] Recently, most image classification studies solicit the intervention of convolutional neural networks because these DL-based classification…
Mohannad Elhamod, Kelly M. Diamond, A. Murat Maga, Yasin Bakis + 7 more
Species classification is an important task that is the foundation of industrial, commercial, ecological, and scientific applications involving the study of species distributions, dynamics, and evolution. While conventional approaches for this task use off-the-shelf machine learning (ML) methods such as existing…
Mauro Tropea, Giuseppe Fedele, Raffaella De Luca, Domenico Miriello + 2 more
'Floriano De Rango' 'Hsiao-Chun Wu'] This paper presents an automatic recognition system for classifying stones belonging to different Calabrian quarries (Southern Italy). The tool for stone recognition has been developed in the SILPI project (acronym of “Sistema per l’Identificazione di Lapidei Per Immagini”)…
Siddharth Srivastava, Prerana Mukherjee, Brejesh Lall
In this paper, we propose a novel approach for feature generation by appropriately fusing KAZE and SIFT features. We then use this feature set along with Minimal Complexity Machine(MCM) for object classification. We show that KAZE and SIFT features are complementary. Experimental results indicate that an elementary…
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…
Francisco Garibaldi-Márquez, Gerardo Flores, Diego A. Mercado-Ravell, Alfonso Ramírez-Pedraza + 2 more
Crop and weed discrimination in natural field environments is still challenging for implementing automatic agricultural practices, such as weed control. Some weed control methods have been proposed. However, these methods are still restricted as they are implemented under controlled conditions. The development of a…
Zhongqi Miao, Kaitlyn M Gaynor, Jiayun Wang, Ziwei Liu + 6 more
In our quest to develop more intelligent machines, knowledge of the visual features used by machines to classify objects shall be helpful. The current state of the art in training machines to classify wildlife species from camera-trap data is to employ convolutional neural networks (CNN) encoded within deep learning…
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…
Yi-Hong Lin, Chih-Ning Tsai, Po-Feng Chen, Yen-Tzu Lin + 5 more
Scanning electrochemical microscopy (SECM) is one of the scanning probe techniques that has attracted considerable attention because of its ability to interrogate surface morphology or electrochemical reactivity. However, the quality of SECM images generally depends on the sizes of the electrodes and many…
Firouz Abdullah Al-Wassai, N. V. Kalyankar
This paper focuses on two main issues; first one is the impact of combination of multi-sensor images on the supervised learning classification accuracy using segment Fusion (SF). The second issue attempts to undertake the study of supervised machine learning classification technique of remote sensing images by using…
Authors not listed
Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR) spectral images, without relying on prior chemical knowledge. The potential of machine learning for chemical…
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…
Dhananjay Bhaskar, Darrick Lee, Hildur Knútsdóttir, Cindy Tan + 4 more
Cell morphology is an important indicator of cell state, function, stage of development, and fate in both normal and pathological conditions. Cell shape is among key indicators used by pathologists to identify abnormalities or malignancies. With rapid advancements in the speed and amount of biological data acquisition…
Alexander E. Siemenn, Eunice Aissi, Fang Sheng, Armi Tiihonen + 3 more
In materials research, the task of characterizing hundreds of different materials traditionally requires equally many human hours spent measuring samples one by one. We demonstrate that with the integration of computer vision into this material research workflow, many of these tasks can be automated, significantly…
Lutz Weber, Aleksei Krasnov, Shadrack Barnabas, Timo Böhme + 1 more
The extraction of chemical information from images, also known as Optical Chemical Structure Recognition (OCSR) has recently gained new attention. This new interest is ignited by various machine learning methods introduced over the last years and the new possibilities to train image models for specific tasks such as…
Hongyang Dong, Simon D.M. Jacques, Winfried Kockelmann, Stephen W. T. Price + 10 more
Hongyang Dong 3 , Simon D.M. Jacques 1 , Winfried Kockelmann 4 , Stephen W. T. Price 1 , Robert Emberson 5 , Dorota Matras 6,7 , Yaroslav Odarchenko 1 , Vesna Middelkoop 10 , Athanasios Giokaris 1 , Olof Gutowski 8 , Ann-Christin Dippel 8 , Martin v. Zimmermann 8 , Andrew M. Beale 3 , Keith T. Butler 9 , Antonis…