A Deep Learning Approach Using Kernel Isolated Pyramid Pooled Visual Geometry Group for Pistachio Type Classification

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Abstract
In the agricultural sector, pistachio classification is crucial for inventory management, quality assurance, and sorting, as it is necessary to differentiate between several pistachio varieties. Deep learning techniques, in particular convolutional neural networks (CNNs), have demonstrated promising results in a variety of areas in image classification tasks in recent years. This work proposes Kernel Isolated Pyramid Pooled VGG16 (KIP-VGG16) to address the multi scale feature pooling of pistachio image for its type classification. This research utilizes the images from Pistachio Image KAGGLE public repository dataset. The initial contribution of this work was the formation of Kernel isolated pistachio image that reduces the interference from background noise and irrelevant features. The second contribution deals with refining the existing VGG16 by replacing the max pooling in the convolution block to pyramid pooling to propose KIP-VGG16 model. The kernel-isolation filtering technique was used that concentrated on extracting the multi-scale features, enabling for more robust feature extraction from images of pistachios under varying conditions. Pyramid pooling was adapted inside the convolution that captures both fine-grained details and global context, ensuring effective representation across varying image sizes and orientations. The KIP-VGG16 model can be applied for tasks where multiple pistachio types need to be identified from complex backgrounds and varying angles. The filtered pistachio images are divided in the ratio of 80: 10:10 and are executed with the CNN and KIP-VGG16 model to assess the performance. Implementation shows that KIP-VGG16 found to exhibit high accuracy of 99.47% towards the classification of Kirmizi and Siirt pistachio classes. This novel KIP-VGG16 method creates new opportunities for high-performance image classification tasks in agriculture, where accurate pistachio type sorting and identification are essential for meeting consumer requests and ensuring product quality.

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