Developing　automatic　garbage　sorting　technologies　will　be　helpful　to　promote　the　construction　of　ecological　civilization　in　China.　A　weighted　convolutional　neural　network　for　the　categorization　of　garbage　images.　First,　a　garbage　image　classification　algorithm　is　implemented　using　a　convolutional　neural　network.　Then,　the　architecture　of　the　network　is　simplified　by　weight　pruning　to　get　rid　of　the　dependency　of　GPU　servers.　In　addition,　a　garbage　image　database　has　been　established　to　train　and　test　the　proposed　algorithm.　The　experimental　results　show　that　the　accuracy　of　proposed　method　can　reach　90.88%　on　the　test　set,　and　the　running　time　of　processing　each　image　takes　78ms.　©　2022　IEEE.