We demonstrated the effectiveness of our approach on a fruits dataset with 63 classes. The obtained results effectively demonstrate the local representation capacity of CNNs. We achieved test set accuracy of 96.63% and training set accuracy of 96.42%, which effectively exemplify the effectiveness of ...
This fruit dataset contains 20 classes of fruit. there are training and testing samples that are images containing single fruit. This fruit dataset supports the manuscript "fruit classification based on weight score level feature fusion" submitted to Journal of Electronic Imaging DOI: 10.13140/RG.2.1...
The project provided a dataset for fruit classification, with 1216 data points and we had to classify the data into one out of 20 labels. Approach We tried to implement several techniques to improve the accuracy of our model. Since the model had more parameters than the number of data ...
effort. In this study, a dataset of a total of 26,149 images of 40 different types of fruits was used for experimentation. The training and test set were randomly recreated and divided into the ratio of 3:1. The experiment introduces a customized head of five different layers into ...
FruitQ: a new dataset of multiple fruit images for freshness evaluation The study provides a benchmarkdataset for the classification task, which could improve research endeavors in the field offruit quality recognition. The ... O Abayomi-Alli,R Damaeviius,S Misra,... - 《Multimedia Tools &...
Version 1.1.0(14.7 MB) byPakize A CNN classification for Apple, Avacado, Banana, Cherry and Orange Follow 0.0 (0) 312 Downloads Updated4 Dec 2023 View License Share Open in MATLAB Online Download This codes trains the "meyve" dataset which consists 5 classes. After classification CNN.m fil...
It corroborates the testament that the classification of citrus fruits is authorita- tive, promising, and adept. Moreover, the potential investigation exhibits a 15% improvement over state-of-the-art approaches, suggesting its potential implemen- tation on a large scale in the food industry for ...
Classification of fruits on the NVIDIA Jetson Nano using TensorFlow. Tested on Jetson Nano but should work on other platforms as well. [...] For classifying anything we need a proper dataset. [...] I made my own dataset, a small one with 6 classes and a total of 600 images (100 fo...
where ‘N’ denotes the size of the sample within the exposure dataset, ‘K’ stands for the count of SNPs, and ' R2’ signifies the fraction of variability accounted for by instrumental variables within said dataset; ' R2’ was calculated using the formula: $$\:{R}^{2}=2\times\:\le...
tomatODis a dataset for tomato fruit localization and ripening classification, containing images of tomato fruits in a greenhouse and high-quality expert annotations from agriculturists. It is a task-specific object detection dataset for tomato fruits, suitable for precision agriculture applications that ...