diff --git a/ethosu/vela/tflite_graph_optimiser.py b/ethosu/vela/tflite_graph_optimiser.py
index 687e5d4..3af8588 100644
--- a/ethosu/vela/tflite_graph_optimiser.py
+++ b/ethosu/vela/tflite_graph_optimiser.py
@@ -827,7 +827,7 @@
     if op.type == Op.FullyConnected:
         # Check if the first dimension indicates batching
         if op.ifm_shapes[0].batch > 1:
-            batching_split = {4: (2, 2), 8: (2, 4), 16: (4, 4)}
+            batching_split = {4: (2, 2), 6: (2, 3), 8: (2, 4), 9: (3, 3), 12: (3, 4), 16: (4, 4)}
             n = op.ifm_shapes[0].batch
             h, w = batching_split.get(n, (1, n))
             op.ifm_shapes[0] = Shape4D([1, h, w, op.ifm_shapes[0].depth])
@@ -840,6 +840,13 @@
             n = op.ofm_shapes[0].batch
             h, w = batching_split.get(n, (1, n))
             op.ofm_shapes[0] = Shape4D([1, h, w, op.ofm_shapes[0].depth])
+            if h == 1 and w > 4:
+                # If batch can not be found in the split set the weights are going to be
+                # read from memory several times. Convert op to conv2d since this
+                # enables weight buffering.
+                op.type = Op.Conv2DBias
+                op.attrs["padding"] = Padding.SAME
+                DebugDatabase.add_optimised(op, op)
     return op