{"doi":"10.52006/main.v3i2.188","title":"Automated Fruit Classification Using Deep Convolutional Neural Network","abstract":"<jats:p>Manual Fruit classification is the traditional way of classifying fruits. It is manual contact-labor that is time-consuming and often results in lesser productivity, inconsistency, and sometimes damaging the fruits (Prabha &amp; Kumar, 2012). Thus, new technologies such as deep learning paved the way for a faster and more efficient method of fruit classification (Faridi &amp; Aboonajmi, 2017). A deep convolutional neural network, or deep learning, is a machine learning algorithm that contains several layers of neural networks stacked together to create a more complex model capable of solving complex problems. The utilization of state-of-the-art pre-trained deep learning models such as AlexNet, GoogLeNet, and ResNet-50 was widely used. However, such models were not explicitly trained for fruit classification (Dyrmann, Karstoft, &amp; Midtiby, 2016). The study aimed to create a new deep convolutional neural network and compared its performance to fine-tuned models based on accuracy, precision, sensitivity, and specificity.</jats:p>","journal":"Philippine Social Science Journal","year":2020,"id":38210,"datarank":0.325845705793167,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"self_citation_contribution":0.24141568686511508,"citation_network_contribution":0.08443001892805192,"self_endowment_contribution":0.24141568686511508,"citer_contribution":0.08443001892805192,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":4,"citers_with_citation_signal":4,"citers_with_endowment":4,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":189915,"name":"El Jireh Bibangco","orcid":"0000-0002-2298-7665","position":1,"is_corresponding":false},{"id":189914,"name":"John Jowil D. Orquia","orcid":"0000-0001-8729-0247","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"18998881","pmcid":null,"openalex_id":"https://openalex.org/W3103566983","authors":[],"funders":[],"total_grants":0,"fwci":0.2312,"citation_percentile":0.70554604,"influential_citations":0,"citation_trend":[{"year":2023,"count":1},{"year":2024,"count":2},{"year":2026,"count":1}],"oa_status":"gold","license":"cc-by-nc","oa_locations":[{"url":"https://philssj.org/index.php/main/article/download/188/171","host_type":"journal"},{"url":"https://doi.org/10.52006/main.v3i2.188","host_type":"GOLD"},{"url":"https://philssj.org/index.php/main/article/download/188/171","host_type":"publisher"},{"url":"https://doaj.org/article/eecde66631094fbebce2e66269be6068","host_type":"repository"}],"fields_of_study":["Smart Agriculture and AI","Computer Science","Agricultural and Food Sciences"],"mesh_terms":[],"keywords":["Convolutional neural network","Deep learning","Artificial intelligence","Computer science","Machine learning","Deep neural networks","Artificial neural network","Pattern recognition (psychology)"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Decent work and economic growth"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-06-11T01:31:42.793260Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}