Evaluation of deep learning model for human activity recognition

Bhat, Owais M.; Khan, Dawood Ashraf

doi:10.1007/s12530-021-09373-6

Cited by 7 publications

(4 citation statements)

References 25 publications

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“…Furthermore, it explains the fundamentals of AdaBoost classification and SVR regression algorithms, as well as the evaluation indices for these algorithms. A book's packaging and design are a reflection of the author's artistic and creative abilities as well as the book's popularity and vitality in the digital age [ 13 ]. Designing more contemporary book packaging begins with simulations that take into account everything from the package itself to the inspection process and even the psychology of the brand itself.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Design of “Shape” and “Meaning” of Book Binding from the Perspective of Deep Learning

Cai²

2022

Computational Intelligence and Neuroscience

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Book binding is the procedure of manually accumulating a book in codex format from a well-ordered pile of paper sheets, which are folded together into sections or occasionally left as a stack of individual sheets. The books undergo binding into different shapes and sizes. Numerous kinds of book bindings are available, each of which comes with its own merits and demerits. Some of them are highly durable, some of them are light-weight, and some of them are attractive. Therefore, it is needed to effectively identify and classify the shape and type of book bindings. With this motivation, this paper develops a butterfly optimization algorithm with a deep learning-enabled book binding classification (BOADL-BBC) model. The major intention of the BOADL-BBC technique is to identify and categorise three different types of book bindings from the input images, namely, hard binding, soft binding, and long-stitch binding. The proposed BOADL-BBC technique initially employs a DL-based Inception v3 model to derive useful feature vectors from the images. For effective classification of book bindings, the BOA with wavelet kernel extreme learning machine (WKELM) model can be applied. The weight and bias values involved in the WKELM model can be effectively adjusted by the use of BOA for book binding classification shows the novelty of the work. To ensure the enhanced performance of the BOADL-BBC technique, a series of simulations were carried out using a set of images that people collected on their own. The experimental results stated that the BOADL-BBC technique has obtained a maximum book binding classification accuracy of 95.56%.

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Section: Introductionmentioning

confidence: 99%

Evaluation of the Design of “Shape” and “Meaning” of Book Binding from the Perspective of Deep Learning

Cai²

2022

Computational Intelligence and Neuroscience

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“…In a narrow sense, aesthetics is a comprehensive product of composition, color, light, and expression of mood and is a discipline that shows natural beauty through painting, color, layout, etc. e purpose of aesthetics is to obtain a sense of natural beauty [12,13]. e use of mathematical models to quantitatively describe aesthetic criteria dates back to 1933.…”

Section: Introductionmentioning

confidence: 99%

“…e basic idea of SVM is to map a low-dimensional data space to a high-dimensional space (Hilbert space) using a nonlinear mapping, which essentially transforms the input low-dimensional data space to a high-dimensional space with the help of a linear transformation (defined by the inner product function) and then finds the optimal hyperplane in this high-dimensional space [13].…”

Section: Introduction To Svr Algorithm Svr Is An Application Of Support Vectors To the Function Regression Problem And Ismentioning

confidence: 99%

Research on Modern Book Packaging Design under Aesthetic Evaluation Based on Deep Learning Model

2021

Discrete Dynamics in Nature and Society

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The development of information technology has led to the rapid development of modern book packaging design. Book packaging design is different from painting. It is a kind of design process that combines artistry and practicality and has double characteristics. With the continuous progress of society, people’s requirements for book packaging design have become higher and higher, and modern book packaging design has become an important topic in the field of art design. To this end, this paper introduces the machine learning algorithms used in this paper, including the AdaBoost algorithm and the SVR algorithm. Specifically, it includes the principles and specific implementation steps for AdaBoost classification algorithm and SVR regression algorithm, as well as evaluation indexes of AdaBoost classification and SVR regression analysis. Realization of physical books reflects artistry, creativity, professionalism, popularity, and vitality of books in the packaging and design of books in the electronic information era. The stimulation effect of this paper starts from packaging design, inspection mechanism, and brand psychology to get the superior design in modern book packaging design.

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“… DHA dataset with CNN-LSTM approach shows best accuracy Acc. Of 96.75% [ 172 ] 2021 Automatically learned features a deep bottleneck multimodal feature fusion (D-BMFF) framework that fused three different modalities of RGB, RGB-D(depth) and 3D coordinates information for activity classification Four RGB-D datasets: UT Kinect, CAD-60, Florence 3D, and SBU Interaction The ARR on UT Kinect, CAD-60, Florence 3D, SBU Interaction are 99%, 98.50%, 98.10%, and 97.75% respectively [ 209 ] 2021 Automatically learned features approach for human activity recognition using ensemble learning of multiple convolutional neural network (CNN) models Ensemble of CNN models gives accuracy of 94% [ 26 ] 2021 Automatically learned features deep learning-based method for human activity recognition problem. The method uses convolutional neural networks to automatically extract features from raw sensor data and classify six basic human activities Diabetes dataset Different activities covered with approximately 90% accuracy using CNN,Random forest, SVM [ 135 ] 2021 Automatically learned features a deep learning architecture that leverages the feature extraction capability of the convolutional neural networks and the construction of the temporal sequences of recurrent neural networks to improve existing classification results Accuracy increased from 30% to 35% due to transfer learning [ 57 ] 2021 Automatically learned features, handcrafted features framework to extract handcrafted high-level motion features and in-depth features by CNN in parallel to recognize human action.…”

Section: Approaches Of Harmentioning

confidence: 99%

A review of vision-based indoor HAR: state-of-the-art, challenges, and future prospects

Bhola

Vishwakarma

2023

Multimed Tools Appl

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With the advent of technology, we are getting more comfortable with the use of gadgets, cameras, etc., and find Artificial Intelligence as an integral part of most of the tasks we perform throughout the day. In such a scenario, the use of cameras and vision-based sensors comes as an escape from many real-time problems and challenges. One major application of these vision-based systems is Indoor Human Activity Recognition (HAR) which serves in a variety of scenarios ranging from smart homes, elderly care, assisted living, and human behavior pattern analysis for identifying any abnormal behavior to abnormal activity recognition like falling, slipping, domestic violence, etc. The effect of HAR in real time has made the area of indoor activity recognition a more explored zone by the industrial segment to attract users with their products in multiple domains. Hence, considering these aspects of HAR, this work proposes a detailed survey on indoor HAR. Through this work, we have highlighted the recent methodologies and their performance in the field of indoor activity recognition. We have also discussed- the challenges, detailed study of approaches with real-world applications of indoor-HAR, datasets available for indoor activity, and their technical details in this work. We have proposed a taxonomy for indoor HAR and highlighted the state-of-the-art and future prospects by mentioning the research gaps and the shortcomings of recent surveys with respect to our work.

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Evaluation of deep learning model for human activity recognition

Cited by 7 publications

References 25 publications

Evaluation of the Design of “Shape” and “Meaning” of Book Binding from the Perspective of Deep Learning

Evaluation of the Design of “Shape” and “Meaning” of Book Binding from the Perspective of Deep Learning

Research on Modern Book Packaging Design under Aesthetic Evaluation Based on Deep Learning Model

A review of vision-based indoor HAR: state-of-the-art, challenges, and future prospects

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