The proceedings contain 43 papers. The special focus in this conference is on Artificial Intelligence and Data Science. The topics include: Challenges in Crop Selection Using machinelearning;Handcrafted Features for ...
ISBN:
(纸本)9783031213847
The proceedings contain 43 papers. The special focus in this conference is on Artificial Intelligence and Data Science. The topics include: Challenges in Crop Selection Using machinelearning;Handcrafted Features for Human Gait recognition: CASIA-A Dataset;local Binary pattern Symmetric Centre Feature Extraction Method for Detection of image Forgery;a Copy and Move image Forged Classification by Using Hybrid Neural Networks;preface;comparative Analysis of Advanced machinelearning Based Techniques to Identify the Lung Cancer: A Review;cardiac Surveillance System Using by the Modified Kalman Filter;an Extensive study on Parkinson’s Disease Using Different Approaches of Supervised learning Algorithms;adaptive Convolution Neural Networks for Facial Emotion recognition;A Gravitational Search Algorithm study on Text Summarization Using NLP;analysis of Deep learning Methods for Prediction of Plant Diseases;ACHM: An Efficient Scheme for Vehicle Routing Using ACO and Hidden Markov Model;detection of Leaf Disease Using Artificial Intelligence;Deep CNN Based Whale Optimization for Predicting the Rice Plant Disease in Real Time;DCBC_DeepL: Detection and Counting of Blood Cells Employing Deep learning and YOLOv5 Model;ML_SPS: stroke Prediction System Employing machinelearning Approach;Classification and Identification of Objects in images Using CNN;a System for Network Based Intrusion Avoidance Using Dedicated machinelearning and Artificial Intelligence-Based Model for Application and Data Safety;AI-Based COVID Alert System on Embedded Platform;an Efficient Detection of Brain stroke Using machinelearning Robust Classification;apple Leaf Diseases Detection System: A Review of the Different Segmentation and Deep learning Methods;underwater image Restoration and Enhancement Based on machine and Deep learning Algorithms.
Braille-a model introduced to reduce the illiteracy rate among the visually challenged people. There has been a lot of scope for the conversion of English language to Braille but, the problem arises when the masses ar...
详细信息
ISBN:
(纸本)9781479984336
Braille-a model introduced to reduce the illiteracy rate among the visually challenged people. There has been a lot of scope for the conversion of English language to Braille but, the problem arises when the masses are unable to understand the communication by the visually challenged people. This paper focuses on the conversion of the Braille code representing Odia language(a language widely spoken in East India) into Odia word as text. For this, imageprocessing using MATLAB technique provides a suitable platform to perform the segmentation of Braille cell for pattern selection and hence, Odia letter and word recognition. Braille Data Base creation acts as a storage system for the process and its accuracy is also tested which is explained in this paper.
Deep learning is a subfield of machinelearning and plays a vital role in the area of imageprocessing, natural language processing, computer vision, etc. As compared to traditional machinelearning methods, it has a ...
详细信息
Digital map processing has been an interest in the imageprocessing and patternrecognition community since the early 80s. With the exponential growth of available map scans in the archives and on the internet, a vari...
详细信息
ISBN:
(纸本)9789811048593;9789811048586
Digital map processing has been an interest in the imageprocessing and patternrecognition community since the early 80s. With the exponential growth of available map scans in the archives and on the internet, a variety of disciplines in the natural and social sciences grow interests in using historical maps as a primary source of geographical and political information in their studies. Today, many organizations such as the United states Geological Survey, David Rumsey Map Collection, ***, and National Library of Scotland, store numerous historical maps in either paper or scanned format. Only a small portion of these historical maps is georeferenced, and even fewer of them have machine-readable content or comprehensive metadata. The lack of a searchable textual content including the spatial and temporal information prevents researchers from efficiently finding relevant maps for their research and using the map content in their studies. These challenges present a tremendous collaboration opportunity for the imageprocessing and patternrecognition community to build advance map processing technologies for transforming the natural and social science studies that use historical maps. This paper presents the potentials of using historical maps in scientific research, describes the current trends and challenges in extracting and recognizing text content from historical maps, and discusses the future outlook.
On the basis of discussing General Feed-Forward Networks (GFFN), a Sequential learning Ahead Masking (SLAM) model and its relevant algorithm for pattern classification are proposed. By adapting this model to the patte...
详细信息
On the basis of discussing General Feed-Forward Networks (GFFN), a Sequential learning Ahead Masking (SLAM) model and its relevant algorithm for pattern classification are proposed. By adapting this model to the pattern classifier, the computer simulation results show that not only the convergence speed and performance of the network are much better than the existing modified BP algorithms, but also the required network scale is greatly reduced. Moreover, Double- Threshold Neuron (DTN) has been applied to SLAM network for pattern classification. The SLAM pattern classifier has been implemented on the domestic micro-neurocomputer CASSANDRA-I and the results are provided as below: For two-class pattern classification problem with 1024 patterns generated randomly in 256-dimensional pattern space, the training time is about 3 hours 20 minutes, and the running time for pattern classification is 0.007 seconds.
Microbes are tiny living organisms beyond the scope to be seen by the naked eye that are coexisting all around the biosphere along with other animals. Significant identification of the microbes from the elementary for...
详细信息
Food monitoring has become an indispensable practice for personal health management in increasingly growing populations. To facilitate this process, advanced imageprocessing and AI technology have empowered automated...
详细信息
ISBN:
(纸本)9783031133213;9783031133206
Food monitoring has become an indispensable practice for personal health management in increasingly growing populations. To facilitate this process, advanced imageprocessing and AI technology have empowered automated recognition of food items and nutrients using food images taken by smart mobile devices. However, precision is often compromised for convenience, which is also applicable in food logging. In this study, we have explored new solutions that can help improve food recognition accuracy with a particular focus on domestic cooking, by leveraging advanced machinelearning and natural language processing techniques, in conjunction with comprehensive food nutrient profiles in the knowledge base, as well as contextual ingredient information parsed from publicly available recipes. The optimized models were proved to be effective and have been integrated into an Android app named "FoodInsight" .
This paper presents content-based image retrieval frameworks with relevance feedback based on AdaBoostlearning method. As we know relevance feedback (RF) is online process. so we have optimized the learning process b...
详细信息
ISBN:
(纸本)9783642240546;9783642240553
This paper presents content-based image retrieval frameworks with relevance feedback based on AdaBoostlearning method. As we know relevance feedback (RF) is online process. so we have optimized the learning process by considering the most positive image selection on each feedback iteration. To learn the system we have used AdaBoost. The main significances of our system are to address the small training sample and to reduce retrieval time. Experiments are conducted on 1856 texture images to demonstrate the effectiveness of the proposed framework. These experiments employed large image databases and combined RCWFs and DT-CWT texture descriptors to represent content of the images.
Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partial-defi...
详细信息
Two efficient edge-detecting operators are introduced. They are both based on templates derived from a 3 x 3 magic square, one operator can obtain edge grodient map with more continuous histogram, and the other can de...
详细信息
ISBN:
(纸本)9781424410651
Two efficient edge-detecting operators are introduced. They are both based on templates derived from a 3 x 3 magic square, one operator can obtain edge grodient map with more continuous histogram, and the other can detect different edge directions efficiently. Experiments implemented based on the fainous standard image Lena have shown the validity of the two approaches. This paper not only presents two efficient approaches for edge detection, but also enlightens new methodology for imageprocessing research based on magic squares.
暂无评论